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2017 EMNLP EMNLP 2017

Efficient Discontinuous Phrase-Structure Parsing via the Generalized Maximum Spanning Arborescence

AbstractWe present a new method for the joint task of tagging and non-projective dependency parsing. We demonstrate its usefulness with an application to discontinuous phrase-structure parsing where decoding lexicalized spines and syntactic derivations is performed jointly. The main contributions of this paper are (1) a reduction from joint tagging and non-projective dependency parsing to the Generalized Maximum Spanning Arborescence problem, and (2) a novel decoding algorithm for this problem through Lagrangian relaxation. We evaluate this model and obtain state-of-the-art results despite strong independence assumptions.

🌉 Interdisciplinary Bridge - Mathematics & Optimization and Natural Language Processing

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